Instructions to use Jethuestad/dat259-nor-wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jethuestad/dat259-nor-wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Jethuestad/dat259-nor-wav2vec2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Jethuestad/dat259-nor-wav2vec2") model = AutoModelForCTC.from_pretrained("Jethuestad/dat259-nor-wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f657ab3e3e129efd60994a5f4803630ac78849b80af4082909a998d47fc38e9
- Size of remote file:
- 1.26 GB
- SHA256:
- c684b9adc5f74d588a4b15983eefabdf735352fd794e9cde0d1a780e5d68767f
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